13,530 research outputs found
PMS30 ADHERENCE TO DULOXETINE AND HOSPITAL UTILIZATION IN PATIENTS WITH MAJOR DEPRESSIVE DISORDER AND CHRONIC PAIN
Influence of annealing on Fermi-level pinning and current transport at Au-Si and Au-GaAs Interfaces
The measurements of internal photoemission and photovoltage within the temperature range of 7-300 K have been performed for unannealed and annealed Au/n-Si and Au/n-GaAs samples. From the internal photoemission measurements, it was observed that annealing at different temperatures does not affect the relativity of interfacial Fermi-level pinning to either the conduction band (for Au/GaAs) or the valence band (for Au/Si) but leads to a significant change of the Schottky barrier height. On the other hand, the photovoltage measurements show that the current transport at the metal/semiconductor interfaces is seriously affected by annealing. © 1995 American Institute of Physics.published_or_final_versio
Interfacial Fermi level and surface band bending in Ni/semi-insulating GaAs contact
For nickel on the chemically clean surface of undoped semi-insulating GaAs at room temperature, an upward surface band bending of 0.062 eV and a barrier height of 0.690 eV have been observed by the photovoltage and the internal photoemission techniques, respectively. The observed surface band bending is in excellent agreement with its predicted value, and the observed barrier height also agrees very well with its value from the very careful analysis of reversed I-V data. It has been determined that the interfacial Fermi level lies at 0.690 eV below the GaAs conduction band minimum at the interface. The interfacial Fermi level is found to coincide with the energy level of the EL2 native defect, indicating the importance of the EL2 in the Fermi level pinning at the interface. © 1995 American Institute of Physics.published_or_final_versio
Characterization of Pt-Si interface by spectroscopic ellipsometry
Spectroscopic ellipsometric measurements for Pt/n-Si samples with different thickness of Pt films have been performed. The thickness of the Pt films determined with the three-phase model (air/Pt/Si) changes with the wavelength λ while that with the four-phase model (air/Pt/interface layer/Si) remains unchanged, showing the existence of an interface layer. At the same time, the apparent optical dielectric constants of the interface layer as a function of λ are also obtained. A calculation based on the effective medium theory is carried out to simulate the optical dielectric data of the interface layer. Some structural information of the interface layer is obtained from the calculation. © 1994 American Institute of Physics.published_or_final_versio
Accelerating exhaustive pairwise metagenomic comparisons
In this manuscript, we present an optimized and parallel version of our previous work IMSAME, an exhaustive gapped aligner for the pairwise and accurate comparison of metagenomes. Parallelization strategies are applied to take advantage of modern multiprocessor architectures. In addition, sequential optimizations in CPU time and memory consumption are provided. These algorithmic and computational enhancements enable IMSAME to calculate near optimal alignments which are used to directly assess similarity between metagenomes without requiring reference databases. We show that the overall efficiency of the parallel implementation is superior to 80% while retaining scalability as the number of parallel cores used increases. Moreover, we also show thats equential optimizations yield up to 8x speedup for scenarios with larger data.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec
A Behavioural Hierarchical Analysis Framework in a Smart Home: Integrating HMM and Probabilistic Model Checking
Smart homes offer great convenience for people living alone and assistance for physically impaired inhabitants. Robust behavioural analysis technology is one of the keys to maximizing the role of the Smart Home. Typically, when it comes to the behavioural analysis of its inhabitants, most researchers have acquired it through data collection from sensors, cameras, and portable Bluetooth sensors. However, a gap in research exists concerning activity recognition in the context of the users physical location in the environment. In this paper, we propose a hierarchical framework based on Hidden Markov Model (HMM) and suggest dividing the behavioural sequence analysis into two layers: spatial transfer and sensor transfer. In addition, we apply probabilistic model checking to verify the properties of each module’s state transfer and obtain the probability of occurrence of the corresponding behavioural sequence. By integrating an implicit Markov model and probabilistic model checking, we effectively analyse the composition and probability of occurrence of three arbitrary sequences of complex behaviours. Finally, anomaly detection and behavioural guidance are discussed based on the proposed behavioural analysis method
Mobile agent path planning under uncertain environment using reinforcement learning and probabilistic model checking
The major challenge in mobile agent path planning, within an uncertain environment, is effectively determining an optimal control model to discover the target location as quickly as possible and evaluating the control system's reliability. To address this challenge, we introduce a learning-verification integrated mobile agent path planning method to achieve both the effectiveness and the reliability. More specifically, we first propose a modified Q-learning algorithm (a popular reinforcement learning algorithm), called Q EA−learning algorithm, to find the best Q-table in the environment. We then determine the location transition probability matrix, and establish a probability model using the assumption that the agent selects a location with a higher Q-value. Secondly, the learnt behaviour of the mobile agent based on Q EA−learning algorithm, is formalized as a Discrete-time Markov Chain (DTMC) model. Thirdly, the required reliability requirements of the mobile agent control system are specified using Probabilistic Computation Tree Logic (PCTL). In addition, the DTMC model and the specified properties are taken as the input of the Probabilistic Model Checker PRISM for automatic verification. This is preformed to evaluate and verify the control system's reliability. Finally, a case study of a mobile agent walking in a grids map is used to illustrate the proposed learning algorithm. Here we have a special focus on the modelling approach demonstrating how PRISM can be used to analyse and evaluate the reliability of the mobile agent control system learnt via the proposed algorithm. The results show that the path identified using the proposed integrated method yields the largest expected reward.</p
Molecular characterization and expression analysis of a hepcidin gene from rice field eel (Monopterus albus)
Hepcidin is a cysteine-rich, dual-function peptide with antimicrobial activity that plays crucial roles in iron homeostasis. A few hepcidin-like genes have been isolated from teleost. Here, we have identified a hepcidin-like gene from rice field eel (RFE), Monopterus albus. Nucleotide sequences including cDNA and genomic DNA (GenBank accession numbers: FJ436808 and FJ594996, respectively) and deduced amino acid sequences were presented. In the 949 bp-long genomic sequence, two introns and three exons were identified. The full-length cDNA encodes a prepropeptide of 90 amino acid residues. RTPCR analysis suggested that hepcidin transcripts are highly abundant in the liver and kidney, less abundant in the heart, skin, brain, blood cells, intestine, spleen and stomach and undetectable in muscle. After challenged with Aeromonas hydrophila infection or iron-dextran stimulation, the hepcidin transcript levels were analyzed by RT-PCR. The results revealed that the expression of hepcidin dramatically increased at 24 h post-infection of the pathogen injection. Moreover, hepcidin mRNAs in the liver, intestine and brain were 2.4, 1.5 and 2-fold increase, respectively, compared with the control animals after 5 days in iron-dextran injected RFEs.Key words: Rice field eel, Monopterus albus, hepcidin, gene expressio
Highly explainable cumulative belief rule-based system with effective rule-base modeling and inference scheme
Structural evolution in synthetic, Ca-based sorbents for carbon capture
The carbonation of CaO-based materials at high temperatures (e.g. > 600°C) is a promising method of capturing CO₂ emitted from, e.g. the combustion of carbonaceous fuels. The resulting CaCO₃ can be regenerated by calcination at a temperature at which the equilibrium partial pressure exceeds that of the local partial pressure of CO₂ (e.g. 950°C). A process involving repeated cycles of carbonation and calcination of a calcareous material is called calcium looping. The capacity of a CaO-based sorbent to accept and reject CO₂ over many cycles is governed by a number of factors, such as chemical composition, surface morphology and pore structure, all of which often evolve with cycling. The present paper investigates the underlying mechanisms controlling the evolution of the micro-structures of a series of synthetic sorbents consisting of CaO mixed with the inert supports Ca₁₂Al₁₄O₃₃ and MgO. These sorbents were subjected to cycles of calcination and carbonation and were characterised using a variety of in situ and ex situ techniques. It was found that the balance between the degree of surface cracking during calcination and the extent of sintering during carbonation was responsible for changes in uptake during cycling, giving an increase in uptake for the supported CaO and a decrease for the unsupported CaO.The authors would like to thank the Australian Synchtrotron for the award of beamtime, and Justin Kimpton and Qinfen Gu for their help with the design and operation of the in situ gas flow capillary XRD cell. Mr Zlatko Zaracevic is acknowledged for the BET measurements. W.L acknowledges funding from the National Research Foundation (NRF), Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. B.G acknowledges the EU Research Fund for Coal and Steel (project number RFCR-CT-2012-00008). M.T.D acknowledges funding from the Cambridge Commonwealth Trusts and Trinity College, Cambridge and the EU ERC for an advanced fellowship for CPG. D.S.S acknowledges financial support by Engineering and Physical Sciences Research Council (EPSRC). C.D.L acknowledges funding by the Australian Research Council (Discovery Projects).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ces.2015.09.01
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